Triple
T15960122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fred Friendly |
E387035
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Friendly |
E550209
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Friendly | Statement: [Fred Friendly, familyName, Friendly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Friendly Context triple: [Fred Friendly, familyName, Friendly]
-
A.
Friendly
chosen
Friendly is the surname of Henry J. Friendly, a highly influential American judge and legal scholar known for his service on the U.S. Court of Appeals for the Second Circuit.
-
B.
FRIENDLY
FRIENDLY is the airline callsign used by Southern Airways Express, a U.S.-based commuter and regional airline.
-
C.
Kind
"Kind" is a studio album by Welsh rock band Stereophonics, showcasing their melodic rock sound and introspective songwriting.
-
D.
Nice
Nice is a prominent Mediterranean coastal city on the French Riviera, known for its mild climate, beaches, and vibrant cultural life.
-
E.
Nice
Nice is a cabin class offered by Breeze Airways that provides a standard, budget-friendly economy experience for passengers.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156fe82d081908b5d41bc5a709de2 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe806ef4819095a4dfe104d0bdc8 |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:53 a.m.